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EP4453261A1 - Signature de cancer du sein épigénétique pronostique/prédictive - Google Patents

Signature de cancer du sein épigénétique pronostique/prédictive

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Publication number
EP4453261A1
EP4453261A1 EP22854712.1A EP22854712A EP4453261A1 EP 4453261 A1 EP4453261 A1 EP 4453261A1 EP 22854712 A EP22854712 A EP 22854712A EP 4453261 A1 EP4453261 A1 EP 4453261A1
Authority
EP
European Patent Office
Prior art keywords
znf92
cancer
expression
biomarkers
inhibitors
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
EP22854712.1A
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German (de)
English (en)
Inventor
Tan A. Ince
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Cornell University
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Cornell University
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Filing date
Publication date
Application filed by Cornell University filed Critical Cornell University
Publication of EP4453261A1 publication Critical patent/EP4453261A1/fr
Pending legal-status Critical Current

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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61K—PREPARATIONS FOR MEDICAL, DENTAL OR TOILETRY PURPOSES
    • A61K31/00—Medicinal preparations containing organic active ingredients
    • A61K31/16—Amides, e.g. hydroxamic acids
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61K—PREPARATIONS FOR MEDICAL, DENTAL OR TOILETRY PURPOSES
    • A61K31/00—Medicinal preparations containing organic active ingredients
    • A61K31/33—Heterocyclic compounds
    • A61K31/395—Heterocyclic compounds having nitrogen as a ring hetero atom, e.g. guanethidine or rifamycins
    • A61K31/435—Heterocyclic compounds having nitrogen as a ring hetero atom, e.g. guanethidine or rifamycins having six-membered rings with one nitrogen as the only ring hetero atom
    • A61K31/44—Non condensed pyridines; Hydrogenated derivatives thereof
    • A61K31/4406—Non condensed pyridines; Hydrogenated derivatives thereof only substituted in position 3, e.g. zimeldine
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61K—PREPARATIONS FOR MEDICAL, DENTAL OR TOILETRY PURPOSES
    • A61K31/00—Medicinal preparations containing organic active ingredients
    • A61K31/33—Heterocyclic compounds
    • A61K31/395—Heterocyclic compounds having nitrogen as a ring hetero atom, e.g. guanethidine or rifamycins
    • A61K31/495—Heterocyclic compounds having nitrogen as a ring hetero atom, e.g. guanethidine or rifamycins having six-membered rings with two or more nitrogen atoms as the only ring heteroatoms, e.g. piperazine or tetrazines
    • A61K31/505—Pyrimidines; Hydrogenated pyrimidines, e.g. trimethoprim
    • A61K31/519—Pyrimidines; Hydrogenated pyrimidines, e.g. trimethoprim ortho- or peri-condensed with heterocyclic rings
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61K—PREPARATIONS FOR MEDICAL, DENTAL OR TOILETRY PURPOSES
    • A61K31/00—Medicinal preparations containing organic active ingredients
    • A61K31/33—Heterocyclic compounds
    • A61K31/395—Heterocyclic compounds having nitrogen as a ring hetero atom, e.g. guanethidine or rifamycins
    • A61K31/55—Heterocyclic compounds having nitrogen as a ring hetero atom, e.g. guanethidine or rifamycins having seven-membered rings, e.g. azelastine, pentylenetetrazole
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61K—PREPARATIONS FOR MEDICAL, DENTAL OR TOILETRY PURPOSES
    • A61K31/00—Medicinal preparations containing organic active ingredients
    • A61K31/60—Salicylic acid; Derivatives thereof
    • A61K31/609—Amides, e.g. salicylamide
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/106—Pharmacogenomics, i.e. genetic variability in individual responses to drugs and drug metabolism
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers

Definitions

  • ZNF92 a generally unexplored transcription factor, is a marker for cancer, including breast cancer. Surprisingly, the extraordinary breast cancer specific over-expression of ZNF92, which is nearly as specific for breast cancer as the estrogen receptor (ER), has not been recognized before.
  • ET-9 and ET-60 Breast cancer gene expression signatures are also described herein that are referred to herein as ET-9 and ET-60, and which unlike most commercially available signatures, are independent of patient age, ethnicity, race, disease stage, metastasis, and radiation therapy, cellular proliferation, tumor subtype and lymph mode metastasis.
  • the high expression of ET-9 and ET-60 signatures are driven by histone deacetylase 7 (HDAC7) and ZNF92.
  • HDAC7 histone deacetylase 7
  • ZNF92 ZNF92.
  • ET-9 and ET-60 signatures are prognostic tests for breast cancer, useful to identify patients with poor outcome, hereby allowing those patients to be treated with additional cycles or combinations of therapies.
  • ET- 9 and ET-60 can be used as a predictive signature to select patients for HDAC inhibitor treatment.
  • the amount of (level of expression of) RNA encoding a polypeptide having SEQ ID NO:1 or a polypeptide having at least 80%, 82%, 85%, 87%, 88%, 89%, 90%, 92%, 94%, 95%, 97%, 98% or 99% amino acid sequence identity thereto, or a portion thereof, in a sample is determined.
  • the amount of RNA encoding a polypeptide having at least two of SEQ ID Ns.3-11 or a polypeptide having at least 80%, 82%, 85%, 87%, 88%, 89%, 90%, 92%, 94%, 95%, 97%, 98% or 99% amino acid sequence identity thereto, or a portion thereof, is determined.
  • the amount of RNA encoding a polypeptide having at least two of SEQ ID Ns.3-11 or a polypeptide having at least 80%, 82%, 85%, 87%, 88%, 89%, 90%, 92%, 94%, 95%, 97%, 98% or 99% amino acid sequence identity thereto, or a portion thereof, is determined.
  • the methods can include treating a subject classified as having poor cancer prognosis, comprising administering one or more histone deacetylase inhibitors, ZNF92 inhibitors, histone demethylase inhibitors, mTOR inhibitors, polo-like kinase inhibitors, heat shock factor inhibitors, or a combination thereof to the subject, wherein the subject is classified has having poor cancer prognosis by measuring expression levels of at least one sample from the subject and determining that the at least one sample has altered expression of the ZNF92, ET-9, or nine or more of the ET-60 biomarkers relative to at least one reference value.
  • the methods can include treating a subject having altered expression of ZNF92, ET-9 biomarkers, or nine or more of the ET-60 biomarkers relative to at least one reference value, by administering one or more histone deacetylase inhibitors, ZNF92 inhibitors, histone demethylase inhibitors, mTOR inhibitors, polo-like kinase inhibitors, heat shock factor inhibitors, or a combination thereof to the subject.
  • One or more reference values can be an average or median of expression levels of at least the ZNF92, ET-9, or ET-60 biomarkers in biological samples from a population of healthy subjects.
  • the subject can have, or be suspected of having, breast cancer, ovarian cancer, colon cancer, brain cancer, pancreatic cancer, prostate cancer, lung cancer, melanoma, leukemia, myeloma, or lymphoma.
  • ZNF92 can be a novel target for development of breast cancer specific treatments.
  • a method can be used for identifying a candidate agent that reduces ZNF92 expression, protein level, or activity. Such a method can include: (a) contacting ZNF92 with a test agent; (b) measuring the expression level or activity of ZNF92; and (c) determining that the test agent reduces the level or activity of ZNF92, to thereby identifying a candidate agent that reduces ZNF92 protein level or activity.
  • FIG.1A Gene Set Enrichment Analysis (GSEA) of HDAC1&7 downstream targets.
  • GSEA Gene Set Enrichment Analysis
  • the top 10 pathways are depicted in the GSEA heatmap, each row represents a unique gene (Entrez ID first column), and each column represents an enriched gene set (p-value range for the top ten pathways 1.47e-11 to 6.5e-16).
  • the blue boxes mark the 86 HDAC1&7 upregulated genes that are associated with each gene set.
  • the analysis is carried out using the online tool.
  • the first column highlights 29 genes associated with ZNF92 binding sites in the promoter (website at www.gsea msigdb.org/gsea/msigdb/collections.jsp).
  • FIG.1B Human Protein Atlas (HPA) Pancancer expression analysis of ZNF92 (website at www.proteinatlas.org/). RNA-seq data from 17 cancer types visualized with box plots, shown as median and 25th and 75th percentiles. Points are displayed as outliers if they are above or below 1.5 times the interquartile range (website at www.proteinatlas.org/ENSG00000146757-ZNF92/pathology).
  • FIG.1C The relative mRNA expression of ZNF92, Estrogen receptor (ERSR1), HER2 (ERBB2) and MYC in the cBioportal TCGA PanCancer dataset that includes 37 tumor types with 10,967 samples (website at www.cbioportal.org/).
  • FIG.1D The relative ZNF92 mRNA expression in the tumor, normal and metastatic tissues in the TNMplot database that has RNA-seq data of TCGA including 730 normal, 9,886 tumor and 394 metastasis samples (website: //tnmplot.com/analysis/).
  • FIGs.2A-2F Breast cancer specific expression of HDCA1&7 downstream targets.
  • HPA Human Protein Atlas
  • FIG.2A PanCancer expression analysis of SNPH (Syna]taphillin)
  • FIG.2B CACNG4 (Calcium voltage-gated channel auxiliary subunit gamma 4)
  • IGFBP5 insulin like growth factor binding protein 5)
  • FIG.2C IGFBP5 (insulin like growth factor binding protein 5)
  • FIG.2D ZNF768 (Zinc Finger Protein 768)
  • BCAS4 breast carcinoma amplified sequence 4)
  • PREX1 phosphatidylinositol-3,4,5- trisphosphate dependent Rac exchange factor 1
  • RNA-seq data from 17 cancer types is visualized with box plots, shown as median and 25th and 75th percentiles. Points are displayed as outliers if they are above or below 1.5 times the interquartile range (see website at www.proteinatlas.org/).
  • FIGs.3A-3H ET-60 prognostic groups compared to other signatures.
  • FIG.3A shows a KM survival chart of ET-60 expression in TCGA, HR: 5.76 (CI: 4.0 –8.2).
  • FIG.3B shows a KM survival chart of 70-gene signature in TCGA (Mammaprint); HR: 4.73 (CI: 3.3 - 6.6); four genes were not found in TCGA Breast invasive carcinoma - July 2016 dataset AA555029_RC, LOC100131053, LOC100288906, LOC730018.
  • FIG.3C shows a KM survival chart of 50-gene signature in TCGA (PAM50/Prosignia), HR: 3.29 (CI: 2.4 - 4.4); all genes found in the dataset.
  • FIG.3D shows a KM survival chart of 25-gene signature (BPMS) in TCGA, HR: 2.64 (CI: 2.0 - 3.4).3 Genes not found in the dataset: ZH3H3, HS3STSB1, PDEC1.
  • FIG.3E shows a Survival KM chart of ET-60 expression in the NKI dataset, HR: 13.39 (CI: 6.1 – 29.2).
  • FIG.3F shows a Time to metastasis KM chart of ET-60 expression in the NKI dataset, HR: 5.76 (CI: 3.8 – 8.5).
  • FIG.3G shows a Time to recurrence KM chart of ET-60 expression in the NKI dataset, HR: 5.58 (CI: 3.7 – 8.2).
  • FIG.3H shows a Time to brain relapse KM chart of ET-60 expression in the SKI dataset, HR: 9.5x10 9 .
  • FIGs 4A-4D ET-9 expression and breast cancer survival
  • FIG.4A shows an expression heatmap of ET-9 genes in the TCGA Breast Invasive Carcinoma mRNA (RNA Seq V2) dataset, including 1,082 patient samples. The subtype classification is provided above the heatmap; basal-like (purple) HER2+ (red), Luminal A (blue), Luminal B (yellow), normal-like (green) (see website at www.cbioportal.org).
  • FIG.4D shows a Kaplan-Meier plot depicting overall free survival of invasive breast carcinoma patients in the TCGA PanCancer dataset.
  • FIGs 5A-5F ET-9 prognostic groups. The Kaplan-Meier survival plots were generated using SurvExpress (see website at bioinformatica.mty.itesm.mx/SurvExpress).
  • FIG.5A graphically illustrates ET-9 overall survival high risk (red), medium risk (green), low risk (blue) tumors, BRCA_TCGA 2016 dataset, HR: 3.04.
  • FIG.5B graphically illustrates ET-9 metastasis high risk (red), medium risk (green), low risk (blue) tumors, NKI dataset, HR: 2.15.
  • FIG.5C graphically illustrates ET-9 brain relapse high risk (red), low risk (green), GSE12276 dataset, HR: 10.95.
  • FIG.5D graphically illustrates 21-gene Oncotype overall survival high risk (red), medium risk (green), low risk (blue) tumors, HR: 3.02.
  • FIG.5E graphically illustrates 12-gene Endopredict overall survival high risk (red), medium risk (green), low risk (blue) tumors, HR: 2.29.
  • FIG.5F graphically illustrates Mao12-gene signature overall survival high risk (red), medium risk (green), low risk (blue) tumors, HR: 2.05.
  • FIGs.6A-6F ET-9 prognostic groups.
  • TNBC Triple negative
  • Kaplan-Meier (KM) charts of relapse free survival of human breast cancer are shown that were generated using Kaplan-Meier plotter [Breast] where high risk is shown as red lines, and low risk is shown as black lines.
  • FIG.7F shows a KM chart of PAM50 (Prosignia) in breast
  • FIG.8A-8C ET-9 (FIGs.8A-8C) and ET-60 (FIGs.8D-8F) prognostic groups in cervix (FIGs.8A and 8D), uterus (FIGs.8B and 8E) and prostate cancer (FIGs.8C and 8F).
  • the Kaplan-Meier survival plots shown in FIG.8 were generated using SurvExpress (see website at bioinformatica.mty.itesm.mx/SurvExpress).
  • FIGs 9A-B show that breast cancer cell line proliferation is inhibited by combination of HDAC, HSP, mTOR, polo-like kinase and Histone demethylase inhibitors.
  • ZNF92, ET-9, and ET-60 are markers useful for detecting, diagnosing, and determining the prognosis of cancer, including breast cancer.
  • Methods for detecting, diagnosing, and determining the prognosis of cancer, including breast cancer, are also described herein.
  • the methods generally involve obtaining a sample from a subject and comparing gene expression levels in the sample with one or more reference values, where the expression levels of the following genes are compared: a ZNF92 gene, ET-9 genes, ET- 60 genes, or a combination of those genes.
  • the method can also include classifying the subject from whom the sample was obtained as having cancer (i.e., being a cancer patient) or not having cancer.
  • the method can also include classifying a cancer patient as having a poor prognosis based upon the expression levels of the ZNF92 gene, ET-9 genes, ET-60 genes, or a combination of those genes in the patient’s sample.
  • the subject is a breast cancer patient.
  • a method for classifying a breast cancer patient according to prognosis can include: (a) comparing the respective levels of expression of a ZNF92 gene, of ET-9 genes, of ET-60 genes, or a combination of the genes in a sample taken from a breast cancer patient to respective reference values of expression of the genes; and (b) classifying the breast cancer patient according to prognosis of his or her breast cancer based on altered expression levels of the ZNF92, the ET-9 genes, nine or more ET-60 genes, or a combination thereof.
  • Samples Breast cancer can be assessed through the evaluation of expression patterns, or profiles, of the ZNF92, ET-9, and ET-60 genes in one or more subject samples.
  • subject, or subject sample refers to an individual regardless of health and/or disease status.
  • a subject can be a subject, a study participant, a control subject, a screening subject, or any other class of individual from whom a sample is obtained and assessed using the markers and/or methods described herein. Accordingly, a subject can be diagnosed with breast cancer, can present with one or more symptoms of breast cancer, or a predisposing factor, such as a family (genetic) or medical history (medical) factor, for breast cancer, can be undergoing treatment or therapy for breast cancer, or the like. Alternatively, a subject can be healthy with respect to any of the aforementioned factors or criteria. It will be appreciated that the term “healthy” as used herein, is relative to breast cancer status, as the term “healthy” cannot be defined to correspond to any absolute evaluation or status.
  • an individual defined as healthy with reference to any specified disease or disease criterion can in fact be diagnosed with any other one or more diseases, or exhibit any other one or more disease criterion, including one or more cancers other than breast cancer.
  • the healthy controls are preferably free of any cancer.
  • the methods for detecting, predicting, and/or assessing the prognosis of breast cancer include collecting a biological sample comprising a cell or tissue, such as a breast tissue sample or a primary breast tumor tissue sample.
  • biological sample is intended any sampling of cells, tissues, or bodily fluids in which expression of ZNF92, ET-9, or ET-60 genes can be detected. Examples of such biological samples include, but are not limited to, biopsies and smears.
  • Bodily fluids useful in the present invention include blood, lymph, urine, saliva, nipple aspirates, gynecological fluids, or any other bodily secretion or derivative thereof.
  • Blood can include whole blood, plasma, serum, or any derivative of blood.
  • the biological sample includes breast cells, particularly breast tissue from a biopsy, such as a breast tumor tissue sample.
  • Biological samples may be obtained from a subject by a variety of techniques including, for example, by scraping or swabbing an area, by using a needle to aspirate cells or bodily fluids, or by removing a tissue sample (i.e., biopsy).
  • a breast tissue sample is obtained by, for example, fine needle aspiration biopsy, core needle biopsy, or excisional biopsy.
  • the samples can be stabilized for evaluating and/or quantifying ZNF92, ET-9, or ET-60 expression levels.
  • fixative and staining solutions may be applied to some of the cells or tissues for preserving the specimen and for facilitating examination.
  • Biological samples, particularly breast tissue samples may be transferred to a glass slide for viewing under magnification.
  • the biological sample is a formalin-fixed, paraffin-embedded breast tissue sample, particularly a primary breast tumor sample.
  • Gene Expression can be used for evaluating and/or quantifying ZNF92, ET-9, or ET-60 expression levels.
  • evaluating and/or quantifying is intended determining the quantity or presence of an RNA transcript or its expression product of ZNF92, ET-9, or ET-60 genes.
  • Methods for detecting expression of the ZNF92, ET-9, or ET-60 genes, including gene expression profiling can involve methods based on hybridization analysis of polynucleotides, methods based on sequencing of polynucleotides, immunohistochemistry methods, and proteomics-based methods. The methods generally involve detect expression products (e.g., mRNA or proteins) encoding by the ZNF92, ET- 9, or ET-60 genes.
  • PCR-based methods which can include reverse transcription PCR (RT-PCR) (Weis et al., TIG 8:263-64, 1992), array-based methods such as microarray (Schena et al., Science 270:467-70, 1995), or combinations thereof are used.
  • microarray is intended an ordered arrangement of hybridizable array elements, such as, for example, polynucleotide probes, on a substrate.
  • probe refers to any molecule that is capable of selectively binding to a specifically intended target biomolecule, for example, a nucleotide transcript or a protein encoded by or corresponding to ZNF92, ET-9, or ET-60 genes.
  • Probes can be synthesized or obtained from ZNF92, ET-9, or ET-60 nucleic acids or they can be derived from appropriate biological preparations. Probes may be specifically designed to be labeled. Examples of molecules that can be utilized as probes include, but are not limited to, RNA, DNA, proteins, antibodies, and organic molecules. Many expression detection methods use isolated RNA. The starting material is typically total RNA isolated from a biological sample, such as a cell or tissue sample, a tumor or tumor cell line, a corresponding normal tissue or cell line, or a combination thereof.
  • RNA e.g., mRNA
  • RNA can be extracted, for example, from stabilized, frozen or archived paraffin-embedded, or fixed (e.g., formalin-fixed) tissue samples (e.g., pathologist-guided tissue core samples).
  • fixed tissue samples e.g., pathologist-guided tissue core samples.
  • RNA extraction from paraffin embedded tissues are disclosed, for example, in Rupp and Locker (Lab Invest.56:A67, 1987) and De Andres et al.
  • RNA isolation can be performed using a purification kit, a buffer set and protease from commercial manufacturers, such as Qiagen (Valencia, Calif.), according to the manufacturer's instructions.
  • Qiagen Valencia, Calif.
  • total RNA from cells can be isolated using Qiagen RNeasy mini-columns.
  • Other commercially available RNA isolation kits include MASTERPURETM Complete DNA and RNA Purification Kit (Epicentre, Madison, Wis.) and Paraffin Block RNA Isolation Kit (Ambion, Austin, Tex.).
  • Total RNA from tissue samples can be isolated, for example, using RNA Stat-60 (Tel-Test, Friendswood, Tex.).
  • RNA prepared from tissue or cell samples e.g.
  • RNA can be used in hybridization or amplification assays that include, but are not limited to, PCR analyses and probe arrays.
  • One method for the detection of RNA levels involves contacting the isolated RNA with a nucleic acid molecule (probe) that can hybridize to the mRNA encoded by the gene being detected.
  • the nucleic acid probe can be, for example, a full-length cDNA, or a portion thereof, such as an oligonucleotide of at least 7, 15, 30, 60, 100, 250, or 500 nucleotides in length and sufficient to specifically hybridize under stringent conditions to any of the ZNF92, ET-9, or ET-60 genes, or any derivative DNA or RNA.
  • Hybridization of an mRNA with the probe indicates that the ZNF92, ET-9, or ET-60 genes in question is being expressed.
  • the mRNA from the sample is immobilized on a solid surface and contacted with a probe, for example by running the isolated mRNA on an agarose gel and transferring the mRNA from the gel to a membrane, such as nitrocellulose.
  • the probes are immobilized on a solid surface and the mRNA is contacted with the probes, for example, in an Agilent gene chip array.
  • Agilent gene chip array A skilled artisan can readily adapt available mRNA detection methods for use in detecting the level of expression of the ZNF92, ET-9, or ET-60 genes.
  • An alternative method for determining the level of ZNF92, ET-9, or ET-60 gene expression in a sample involves the process of nucleic acid amplification of the ZNF92, ET-9, or ET-60 mRNA (or cDNA thereof), for example, by RT-PCR (U.S. Pat. No. 4,683,202), ligase chain reaction (Barany, Proc. Natl. Acad. Sci.
  • ZNF92, ET-9, or ET-60 gene expression is assessed by quantitative RT-PCR.
  • Numerous different PCR or QPCR protocols are available and can be directly applied or adapted for use using the ZNF92, ET-9, or ET-60 genes.
  • a target polynucleotide sequence is amplified by reaction with at least one oligonucleotide primer or pair of oligonucleotide primers.
  • the primer(s) hybridize to a complementary region of the target nucleic acid and a DNA polymerase extends the primer(s) to amplify the target sequence.
  • a nucleic acid fragment of one size dominates the reaction products (the target polynucleotide sequence which is the amplification product).
  • the amplification cycle is repeated to increase the concentration of the single target polynucleotide sequence.
  • the reaction can be performed in any thermocycler commonly used for PCR.
  • cyclers with real-time fluorescence measurement capabilities for example, SMARTCYCLER® (Cepheid, Sunnyvale, Calif.), ABI PRISM 7700® (Applied Biosystems, Foster City, Calif.), ROTOR-GENETM (Corbett Research, Sydney, Australia), LIGHTCYCLER® (Roche Diagnostics Corp, Indianapolis, Ind.), ICYCLER® (Biorad Laboratories, Hercules, Calif.) and MX4000® (Stratagene, La Jolla, Calif.).
  • Quantitative PCR QPCR
  • QPCR also referred as real-time PCR
  • QPCR gene measurement can be applied to standard formalin-fixed paraffin-embedded clinical tumor blocks, such as those used in archival tissue banks and routine surgical pathology specimens (Cronin et al. (2007) Clin Chem 53:1084-91)[Mullins 2007] [Paik 2004].
  • quantitative PCR or “real time QPCR” refers to the direct monitoring of the progress of PCR amplification as it is occurring without the need for repeated sampling of the reaction products.
  • the reaction products may be monitored via a signaling mechanism (e.g., fluorescence) as they are generated and are tracked after the signal rises above a background level but before the reaction reaches a plateau.
  • a signaling mechanism e.g., fluorescence
  • the number of cycles required to achieve a detectable or “threshold” level of fluorescence varies directly with the concentration of amplifiable targets at the beginning of the PCR process, enabling a measure of signal intensity to provide a measure of the amount of target nucleic acid in a sample in real time.
  • microarrays are used for expression profiling. Microarrays are particularly well suited for this purpose because of the reproducibility between different experiments. DNA microarrays provide one method for the simultaneous measurement of the expression levels of large numbers of genes.
  • Each array consists of a reproducible pattern of capture probes attached to a solid support. Labeled RNA or DNA is hybridized to complementary probes on the array and then detected by laser scanning. Hybridization intensities for each probe on the array are determined and converted to a quantitative value representing relative gene expression levels. See, for example, U.S. Pat. Nos. 6,040,138, 5,800,992 and 6,020,135, 6,033,860, and 6,344,316. High-density oligonucleotide arrays are particularly useful for determining the gene expression profile for a large number of RNAs in a sample. Techniques for the synthesis of these arrays using mechanical synthesis methods are described in, for example, U.S. Pat. No. 5,384,261.
  • arrays can be nucleic acids (or peptides) on beads, gels, polymeric surfaces, fibers (such as fiber optics), glass, or any other appropriate substrate. See, for example, U.S. Pat. Nos.5,770,358, 5,789,162, 5,708,153, 6,040,193 and 5,800,992. Arrays can be packaged in such a manner as to allow for diagnostics or other manipulation of an all-inclusive device. See, for example, U.S. Pat. Nos.5,856,174 and 5,922,591.
  • PCR amplified inserts of cDNA clones can be applied to a substrate in a dense array.
  • the microarrayed genes, immobilized on the microchip, are suitable for hybridization under stringent conditions.
  • Fluorescently labeled cDNA probes can be generated through incorporation of fluorescent nucleotides by reverse transcription of RNA extracted from tissues of interest.
  • Labeled cDNA probes applied to the chip hybridize with specificity to each spot of DNA on the array. After stringent washing to remove non-specifically bound probes, the chip is scanned by confocal laser microscopy or by another detection method, such as a CCD camera. Quantitation of hybridization of each arrayed element allows for assessment of corresponding mRNA abundance.
  • cDNA probes generated from two sources of RNA can be hybridized pairwise to the array.
  • the relative abundance of the transcripts from the two sources corresponding to each specified gene is thus determined simultaneously.
  • a miniaturized scale can be used for the hybridization, which provides convenient and rapid evaluation of the expression pattern for large numbers of genes.
  • Such methods have been shown to have the sensitivity required to detect rare transcripts, which are expressed at a few copies per cell, and to reproducibly detect at least approximately two-fold differences in the expression levels (Schena et al., Proc. Natl. Acad. Sci. USA 93:106-49, 1996).
  • Microarray analysis can be performed by commercially available equipment, following manufacturer's protocols, such as by using the Affymetrix GenChip technology, or Agilent ink jet microarray technology.
  • level refers to a measure of the amount of, or a concentration of a transcription product, for instance an mRNA, or a translation product, for instance a protein or polypeptide.
  • activity refers to a measure of the ability of a transcription product or a translation product to produce a biological effect or to a measure of a level of biologically active molecules.
  • expression level further refer to gene expression levels or gene activity.
  • Gene expression can be defined as the utilization of the information contained in a gene by transcription and translation leading to the production of a gene product.
  • the terms “increased,” or “increase” in connection with expression of the biomarkers described herein generally means an increase by a statically significant amount.
  • the terms “increased” or “increase” means an increase of at least 10% as compared to a reference value, for example an increase of at least about 20%, or at least about 30%, or at least about 40%, or at least about 50%, or at least about 60%, or at least about 70%, or at least about 80%, or at least about 90% or up to and including a 100% increase or any increase between 10-100% as compared to a reference value or level, or at least about a 1.5-fold, at least about a 1.6-fold, at least about a 1.7-fold, at least about a 1.8-fold, at least about a 1.9-fold, at least about a 2-fold, at least about a 3-fold, or at least about a 4-fold, or at least about a 5-fold, at least about a 10-fold increase, any increase between 2-fold and 10-fold, at least about a 25-fold increase, or greater as compared to a reference level.
  • an increase is at least about 1.8-fold increase over a reference value.
  • the terms “decrease,” or “reduced,” or “reduction,” or “inhibit” in connection with expression of the biomarkers described herein generally to refer to a decrease by a statistically significant amount.
  • “reduced”, “reduction” or “decrease” or “inhibit” means a decrease by at least 10% as compared to a reference level, for example a decrease by at least about 20%, or at least about 30%, or at least about 40%, or at least about 50%, or at least about 60%, or at least about 70%, or at least about 80%, or at least about 90% or up to and including a 100% decrease (e.g.
  • a “reference value” is a predetermined reference level, such as an average or median of expression levels of each of ZNF92, ET-9, or ET-60 biomarkers in, for example, biological samples from a population of healthy subjects.
  • the reference value can be an average or median of expression levels of each of ZNF92, ET-9, or ET-60 biomarkers in a chronological age group matched with the chronological age of the tested subject.
  • the reference biological samples can also be gender matched.
  • the reference biological samples can also be cancer containing tissue from a specific subgroup of patients, such as stage 1, stage 2, stage 3, or grade 1, grade 2, grade3 cancers, non-metastatic cancers, untreated cancers, hormone treatment resistant cancers, HER2 amplified cancers, triple negative cancers, estrogen negative cancers, or other relevant biological or prognostic subsets.
  • malignancy associated response signature expression levels in a sample can be assessed relative to normal breast tissue from the same subject or from a sample from another subject or from a repository of normal subject samples.
  • biomarker expression is said to be “increased” or “decreased,” respectively, as those terms are defined herein.
  • Exemplary analytical methods for classifying expression of a biomarker, determining a malignancy associated response signature status, and scoring of a sample for expression of a malignancy associated response signature biomarker are explained in detail herein. Treatment Methods are described herein for treating cancer. Such methods can involve administering therapeutic agents that can treat cancers with poor prognosis.
  • the cancer includes breast cancer, ovarian cancer, colon cancer, brain cancer, pancreatic cancer, prostate cancer, lung cancer, or melanoma.
  • the cancer includes leukemia, myeloma, or lymphoma.
  • the methods can include downregulating expression of one or more of the following: ZNF92, histone deacetylase, histone demethylase, mTOR, polo-like kinase, proteins with heat shock factors, any of the ET-9 biomarkers, any of the ET-60 biomarkers, or a combination thereof.
  • Suitable methods for downregulating such expression can include: inhibiting transcription of mRNA; degrading mRNA by methods including, but not limited to, the use of interfering RNA (RNAi); blocking translation of mRNA by methods including, but not limited to, the use of antisense nucleic acids or ribozymes, or the like.
  • a suitable method for downregulating expression may include providing to the cancer a small interfering RNA (siRNA) targeted to ZNF92, histone deacetylase, histone demethylase, mTOR, polo-like kinase, proteins with heat shock factors, any of the ET-9 biomarkers, any of the ET-60 biomarkers, or a combination.
  • siRNA small interfering RNA
  • Suitable methods for down-regulating the function or activity of ZNF92, histone deacetylase, histone demethylase, mTOR, polo-like kinase, proteins with heat shock factors, any of the ET-9 biomarkers, any of the ET-60 biomarkers, or a combination thereof may include administering a small molecule inhibitor that inhibits the function or activity of any of these markers or factors.
  • one or more histone deacetylase inhibitors can be administered to treat cancers with poor prognosis, such as cancers identified by measuring and/or monitoring ZNF92, any of the ET-9 biomarkers, and/or any of the ET-60 biomarkers described herein.
  • histone deacetylase inhibitors are not administered to treat cancers with poor prognosis, such as cancers identified by measuring and/or monitoring ZNF92, any of the ET-9 biomarkers, and/or any of the ET-60 biomarkers described herein
  • a “Histone Deacetylase inhibitor” or “HDAC inhibitor” refers to inhibitors of Histone Deacetylase 1 (HDAC1), Histone Deacetylase 7 (HDAC7), and/or phosphorylated HDAC7, including agents that inhibit the level and/or activity of HDAC1 and/or HDAC7 and/or phosphorylated HDAC7, as well as agents that inhibit the phosphorylation of HDAC7 e.g., inhibitors of EMK protein kinase, C-TAK1 protein kinase, and/or CAMK protein kinase, and agents that activate or increase the level and/or activity of phosphatase activity to remove phosphoryl groups from HDAC7, e.g.
  • HDAC inhibitors include molecules that bind directly to a functional region of HDAC1 and/or HDAC7 and/or phosphorylated HDAC7 in a manner that interferes with the enzymatic activity of HDAC1 and/or HDAC7 and/or phosphorylated HDAC7 e.g., agents that interfere with substrate binding to HDAC1 and/or HDAC7 and/or phosphorylated HDAC7.
  • HDAC inhibitors include molecules that bind directly to HDAC7 in a manner that prevents the phosphorylation of HDAC7.
  • HDAC inhibitors include agents that inhibit the activity of peptides, polypeptides, or proteins that modulate the activity of HDAC1 and/or HDAC7 e.g., inhibitors of EMK protein kinase, C-TAK1 kinase, CAMK protein kinase inhibitors of C-TAK1 protein kinase.
  • suitable inhibitors include, but are not limited to antisense oligonucleotides, oligopeptides, interfering RNA e.g., small interfering RNA (siRNA), small hairpin RNA (shRNA), aptamers, ribozymes, small molecule inhibitors, or antibodies or fragments thereof, and combinations thereof.
  • HDAC inhibitors are specific inhibitors or specifically inhibit the level and/or activity of HDAC1 and/or HDAC7 and/or phosphorylated HDAC7.
  • specific inhibitor(s) refers to inhibitors characterized by their ability to bind to with high affinity and high specificity to HDAC1 and/or HDAC7 and/or phosphorylated HDAC7 proteins or domains, motifs, or fragments thereof, or variants thereof, and preferably have little or no binding affinity for non-HDAC1 and/or non-HDAC7 and/or non-phosphorylated HDAC7 proteins.
  • telomere kinase As used herein, “specifically inhibit(s)” refers to the ability of an HDAC inhibitor of the present invention to inhibit the level and/or activity of a target polypeptide, e.g., HDAC1, and/or HDAC7, and/or phosphorylated HDAC7, and/or EMK protein kinase, and/or C-TAK1 protein kinase and/or CAMK protein kinase and preferably have little or no inhibitory effect on non-target polypeptides.
  • a target polypeptide e.g., HDAC1, and/or HDAC7, and/or phosphorylated HDAC7, and/or EMK protein kinase, and/or C-TAK1 protein kinase and/or CAMK protein kinase and preferably have little or no inhibitory effect on non-target polypeptides.
  • specifically activate(s) and “specifically increase(s)” refers to the ability of an HDAC inhibitor of the present invention to stimulate (e.g., activate or increase) the level and/or activity of a target polypeptide, e.g., PP2A phosphatase and/or myosin phosphatase and preferably to have little or no stimulatory effect on non-target polypeptides.
  • a target polypeptide e.g., PP2A phosphatase and/or myosin phosphatase and preferably to have little or no stimulatory effect on non-target polypeptides.
  • HDAC inhibitors include Vorinostat (SAHA), Entinostat (MS-275), Panobinostat (LBH589), Trichostatin A (TSA), Mocetinostat (MGCD0103), 4- Phenylbutyric acid (4-PBA), ACY-775, Belinostat (PXD101), Romidepsin (FK228, Depsipeptide), MC1568, Tubastatin A HCl, Givinostat (ITF2357), Dacinostat (LAQ824), CUDC-101, Quisinostat (JNJ-26481585) 2HCl, Pracinostat (SB939), PCI-34051, Droxinostat, Abexinostat (PCI-24781), RGFP966, AR-42, Ricolinostat (ACY-1215), Valproic Acid (NSC 93819) sodium salt, Tacedinaline (CI994), Fimepinostat (CUDC- 907), Sodium butyrate, Curcumin
  • one or more histone demethylase inhibitors can be administered to treat cancers with poor prognosis, such as cancers identified by measuring and/or monitoring ZNF92, any of the ET-9 biomarkers, and/or any of the ET-60 biomarkers described herein.
  • histone demethylase inhibitors examples include GSK-J4, 2,4- Pyridinedicarboxylic Acid, AS8351, Clorgyline hydrochloride, CPI-455, Daminozide, GSK-2879552, GSK-J1, GSK-J2, GSK-J5, GSK-LSD1, IOX1, IOX2, JIB-04, ML-324, NCGC00244536, OG-L002, ORY-1001, SP-2509, TC-E 5002, UNC-926, ⁇ -Lapachone, or combinations thereof.
  • Such inhibitors are available, e.g., from Selleckchem.com.
  • one or more mTOR inhibitors can be administered to treat cancers with poor prognosis, such as cancers identified by measuring and/or monitoring ZNF92, any of the ET-9 biomarkers, and/or any of the ET-60 biomarkers described herein.
  • mTOR inhibitors include Rapamycin (AY-22989), Everolimus (RAD001), AZD8055, Temsirolimus (CCI-779), PI-103, NU7441 (KU-57788), KU-0063794, Torkinib (PP242), Ridaforolimus (Deforolimus, MK-8669), Sapanisertib (MLN0128), Voxtalisib (XL765) Analogue, Torin 1, Omipalisib (GSK2126458), OSI-027, PF- 04691502, Apitolisib (GDC-0980), GSK1059615, WYE-354, Gedatolisib (PKI-587), Vistusertib (AZD2014), Torin 2, WYE-125132 (WYE-132), BGT226 (NVP-BGT226) maleate, Palomid 529 (P529), PP121, WYE-687, Clemastine (HS-592)
  • PLK inhibitors are available from Selleckchem.com.
  • one or more Polo-Like Kinase (PLK) inhibitors can be administered to treat cancers with poor prognosis, such as cancers identified by measuring and/or monitoring ZNF92, any of the ET-9 biomarkers, and/or any of the ET- 60 biomarkers described herein.
  • PLK inhibitors examples include BI 2536, Volasertib (BI 6727), Wortmannin (KY 12420), Rigosertib (ON-01910), GSK461364, HMN-214, MLN0905, Ro3280, SBE 13 HCl, Centrinone (LCR-263), CFI-400945, HMN-176, Onvansertib (NMS-P937), or combinations thereof.
  • one or more heat shock factor inhibitors can be administered to treat cancers with poor prognosis, such as cancers identified by measuring and/or monitoring ZNF92, any of the ET-9 biomarkers, and/or any of the ET-60 biomarkers described herein.
  • heat shock factor inhibitors include one or more of the following Tanespimycin (17-AAG), Pimitespib (TAS-116, Luminespib (NVP-AUY922), Alvespimycin (17-DMAG) HCl, Ganetespib (STA-9090), Onalespib (AT13387), Geldanamycin (NSC 122750), SNX-2112 (PF-04928473), PF-04929113 (SNX-5422), KW-2478, Cucurbitacin D, VER155008, VER-50589, CH5138303, VER-49009, NMS-E973, Zelavespib (PU-H71), HSP990 (NVP-HSP990) , XL888 NVP-BEP800, BIIB021or a combination thereof.
  • solid tumor is intended to include, but not be limited to, the following sarcomas and carcinomas: fibrosarcoma, myxosarcoma, liposarcoma, chondrosarcoma, osteogenic sarcoma, chordoma, angiosarcoma, endotheliosarcoma, lymphangiosarcoma, lymphangioendotheliosarcoma, synovioma, mesothelioma, Ewing's tumor, leiomyosarcoma, rhabdomyosarcoma, colon carcinoma, pancreatic cancer, breast cancer, ovarian cancer, prostate cancer, squamous cell carcinoma, basal cell carcinoma, adenocarcinoma, sweat gland carcinoma, sebaceous gland carcinoma, papillary carcinoma, papillary adenocarcinomas, cystadenocarcinoma, medullary carcinoma, bronch
  • ZNF92 Zinc Finger Protein
  • ZNF92 Zinc Finger Protein
  • the ZNF92 gene is located on chromosome 7 (Gene ID: 168374; location NC_000007.14 (65373855..65401136).
  • An example of an amino acid sequence for ZNF92 isoform 1 is available as UNIPROT accession no. Q03936-1 and shown below as SEQ ID NO:1.
  • BC040594.1 shown below as SEQ ID NO:2 1 CTCTCGCTGC AGCCGGCGCT CCACGTCTAG TCTTCACTGC 41 TCTGCGTCCT GTGCTGATAA AGGCTCGCCG CTGTGACCCT 81 GTTACCTGCA AGAACTTGGA GGTTCACAGC TAAGACGCCA 121 GGACCCCCTG GAAGCCTAGA AATGGGACCA CTGACATTTA 161 GGGATGTGAA AATAGAATTC TCTCTAGAGG AATGGCAATG 201 CCTGGACACT GCGCAGCGGA ATTTATATAG AGATGTGATG 241 TTAGAGAACT ACAGAAACCT GGTCTTCCTT GGTATTGCTG 281 TCTCTAAGCC AGACCTGATC ACCTGGCTGG AGCAAGGAAA 321 AGAGCCCTGG AATCTGAAGA GACATGAGAT GGTAGACAAA 361 ACCCCAGTTA TGTGTTCTCA TTTTGCCCAA GATGTTTGGC 401 CAGAGCACAG
  • Table 1 ET-9 signature genes Entrez ID ET-9 Name & Example of Human Amino Acid Sequence Entrez ID ET-9 Name & Example of Human Amino Acid Sequence Entrez ID ET-9 Name & Example of Human Amino Acid Sequence Entrez ID ET-9 Name & Example of Human Amino Acid Sequence Entrez ID ET-9 Name & Example of Human Amino Acid Sequence Entrez ID ET-9 Name & Example of Human Amino Acid Sequence Entrez ID ET-9 Name & Example of Human Amino Acid Sequence Table 2: ET-60 signature genes ID ET-60 Name & Example of Human Amino Acid Sequence ID ET-60 Name & Example of Human Amino Acid Sequence ID ET-60 Name & Example of Human Amino Acid Sequence ID ET-60 Name & Example of Human Amino Acid Sequence ID ET-60 Name & Example of Human Amino Acid Sequence ID ET-60 Name & Example of Human Amino Acid Sequence ID ET-60 Name & Example of Human Amino Acid Sequence ID ET-60 Name & Example of Human Amino Acid Sequence ID ET
  • Such isoforms and variants can have sequences with between 65-100% sequence identity to a reference sequence, for example with at least at least 65%, at least 70%, at least 80%, at least 90%, at least 95%, at least 96%, at least 97% sequence, at least 98%, at least 99%, or at least 99.5% identity to a sequence described herein or a reference sequence (such as one described in the NCBI or Uniprot databases) over a specified comparison window.
  • Optimal alignment may be ascertained or conducted using the homology alignment algorithm of Needleman and Wunsch, J. Mol. Biol.48:443-53 (1970).
  • the “absolute amplitude” of correlation expressions means the distance, either positive or negative, from a zero value; i.e., both correlation coefficients ⁇ 0.35 and 0.35 have an absolute amplitude of 0.35.
  • ZNF92, ET-9, or ET-60 genes “Status” means a state of gene expression of a set of genetic markers whose expression is strongly correlated with a particular phenotype.
  • ZNF92 status means a state of gene expression of a set of genetic markers (e.g., ET-9 or ET-60 markers) whose expression is strongly correlated with that of the ZNF92 gene, wherein the expression pattern of these (e.g.
  • ET-9 or ET-60 can differ detectably between tumors expressing the ZNF92 and tumors not expressing ZNF92.
  • “Good prognosis” means that a patient is expected to have longer overall survival (OS), or progression –free survival (PFS), or disease-specific survival (DSS) or recurrence-free survival (RFS) compared to “poor prognosis” patients.
  • OS overall survival
  • PFS progression –free survival
  • DSS disease-specific survival
  • RFS recurrence-free survival
  • OS overall survival
  • PFS progression-free survival
  • DFS disease-specific survival
  • RFS recurrence-free survival
  • DFS disease-specific survival
  • RFS recurrence-free survival
  • Marker means an entire gene, mRNA, EST, or a protein product derived from that gene, where the expression or level of expression changes under different conditions, where the expression of the gene (or combination of genes) correlates with a certain condition, the gene or combination of genes is a marker for that condition.
  • Marker-derived polynucleotides means the RNA transcribed from a marker gene, any cDNA, or cRNA produced therefrom, and any nucleic acid derived therefrom, such as synthetic nucleic acid having a sequence derived from the gene corresponding to the marker gene.
  • a “similarity value” is a number that represents the degree of similarity between two things being compared.
  • a similarity value may be a number that indicates the overall similarity between a patient's expression profile using specific phenotype-related markers and a control specific to that phenotype (for instance, the similarity to a “good prognosis” template, where the phenotype is a good prognosis).
  • the similarity value may be expressed as a similarity metric, such as a correlation coefficient, or may simply be expressed as the expression level difference, or the aggregate of the expression level differences, between a patient sample and a template.
  • Example 1 HDAC1 and HDAC7 co-regulated genes HDAC1 and HDAC7 each regulate over 3,000 to 5,000 genes in different breast cancer cells, making the analysis of their downstream targets challenging.
  • gene set enrichment analysis GSEA was used to identify overlap among expression signatures that could be used to reveal underlying biological processes.
  • MSigDB Molecular Signatures Database
  • SE HDAC1/7-superenhancer
  • HDAC1/7-SE upregulated targets such as SNPH, CCANG4, PREX1, IGFBP5, IL34 and BCAS4 also demonstrate remarkable level of breast cancer associated overexpression, providing additional support for the relevance of the ET-9 and ET-60 signatures (FIG.2).
  • Example 3 ET-60 and ET-9 Signatures
  • the inventors then determined that a sixty gene subset of the HDAC1&7-SE upregulated genes, including 22 targets of ZNF-92, referred to herein as Epigenetic Tumor (ET-60) signature (Table 2) correlated significantly with breast cancer patient outcome as analyzed by using SurvExpress online tools (see website at (bioinformatica.mty.itesm.mx:8080/Biomatec/SurvivaXvalidator.jsp) (Aguirre-Gamboa et al.; 8 (9), e74250, PLoS One, 2013).
  • E-60 Epigenetic Tumor
  • the hazard ratio is defined as a comparison between the probability of events in a treatment group, compared to the probability of events in a control group. For example, a hazard ratio of 3 means that three times the number of events are seen in the treatment group at any point in time.
  • the inventors identified the nine-gene subset from the initial sixty-eight genes, henceforth referred as Epigenetic Tumor (ET-9) signature (Table 1).
  • E-9 Epigenetic Tumor
  • TCGA Breast Invasive Carcinoma
  • PanCancer Atlas Breast Invasive Carcinoma
  • Example 4 Altered ET-9 Signature is Prognostic of Shorter Survival This Example illustrates that the ET-9 signature can be used to identify which subjects (e.g., breast cancer patients) have a poor prognosis, thereby indicating that those subjects should have further treatment. Methods Two different software packages were used to analyze the survival data, SurvExpress and Kaplan-Meier Plotter. The prognostic significance of the ET-9 genes was individually analyzed using metasurvival analysis (see website at gent2.appex.kr/gent2/; Park et al. BMC Med Genomics 12 (Suppl 5) 101, 2019).
  • the SurvExpress analysis was carried out selecting; (a) censored survival days, (b) without stratification, (c) heat map by prognostic index, (d) Network none, (e) no imputation, (f) no quantization (g) advanced check, (h) attribute plot check with default options for other variables.
  • two or three risk groups were selected, which were determined by prognostic index (risk score) estimated by beta coefficients multiplied by gene expression values.
  • the risk groups are split by the median of the prognostic index generating risk groups of the similar number of samples.
  • T3 or Q1 vs Q4 which involves assigning the data into three cohorts and then omit the middle cohort, or (c) using the best available cut-off value.
  • the results shown are with the best available cut-off value.
  • cut-off value is used as the best cutoff to separate the input data into two groups.”
  • the tutorial further stated, “In case the generated cut-off values are ambiguous (e.g., multiple cut-off values deliver very low P values), the cut-off value corresponding to the highest HR is used” (Lánczky, András, and Balázs Gy ⁇ rffy. “Web-Based Survival Analysis Tool Tailored for Medical Research (KMplot): Development and Implementation.” Journal of medical Internet research vol. 23,7 e27633. 26 Jul. 2021, doi:10.2196/27633).
  • the BIC_TCGA and METABRIC datasets include 2,988 patients with over 20 years of follow up (cBioPortal) (Gao et al.
  • Example 5 Proliferation signature Even in the era of molecular diagnostics, the histological grading of breast cancer remains to be one of the most powerful prognostic tools. For example, the relative hazard ratio between grade I vs.
  • the breast cancer grading system combines three attributes of tumors: (i) the mitotic count as a measure of proliferation, (ii) the extent of tubule formation as a measure of architectural tissue differentiation, and (iii) the degree of nuclear pleomorphism as a measure of cellular differentiation.
  • Example 6 Breast cancer subtype and stage Although, the grade and lymph node stage are still powerful prognostic features of breast cancer (Johansson et al.; 23 (1), 17, Breast Cancer Res, 2021), existing commercial prognostic signatures (Oncotype DX, Prosignia, Endopredict) are useful only in early stage, small ER-positive/HER-negative and lymph node-negative breast cancers (Nunes et al.
  • ER-positive breast cancers include high-grade tumors with increased proliferative index that have a worse outcome compared to low grade ER-positive tumors with a low proliferation rate.
  • prognostic signatures have been associated with proliferation, their ability to identify ER-positive tumors with high proliferation index is not surprising.
  • the prognostic power of proliferation may be more limited in other subtypes of breast cancer.
  • ET-60 and ET-9 in multiple combined breast datasets using K-M plotter (kmplot.com/analysis/) (Lanczky and Gyorffy; 23 (7), e27633, J Med Internet Res, 2021)] and have shown that ET-9 and ET-60 signatures are predictive of worse survival outcome in other breast cancer subtypes such as HER-positive, ER- negative, Lymph Node positive, and post-chemotherapy breast cancers. These results indicate that ET-9 and ET-60 signatures do not overlap with existing commercial signatures and may have a broader and complimentary utility (FIG.6E-6F and FIG.7).
  • Example 7 Other Cancer Types It was examined whether ET-60 or ET-9 signatures may be prognostic in other cancer types.
  • Example 8 Drug response The breast cancer cell lines BT20, MDA-MB-231 and SUM-159 were treated with HDAC inhibitor (MS275), HSP inhibitor (17-AAG), mTOR inhibitor (Niclosamide), polo-like kinase inhibitor (BI2536) and histone demethylase inhibitor (GSK-J4).
  • HDAC inhibitor MS275
  • HSP inhibitor 17-AAG
  • mTOR inhibitor Niclosamide
  • polo-like kinase inhibitor BI2536
  • GSK-J4 histone demethylase inhibitor
  • the disclosure provides a pharmaceutical composition comprising two or more of a histone deacetylase inhibitor, a ZNF92 inhibitor, a histone demethylase inhibitor, a mTOR inhibitor, a polo-like kinase (PLK) inhibitor, or a heat shock factor inhibitor.
  • Table 6 List of tumor types and samples in the TCGA PanCancer dataset Study Abbreviation TCGA Study Name 1 ACC Adrenocortical carcinoma a Table 7A: List of breast cancer molecular signatures tested in cBioPortal for Cancer Genomics survival analysis (cbioportal.org/) Oncogene Pathways Signature Tested ADGRG1 (GPR56) CACNG4 CCDC69 CX3CL1 FIBCD1 GDPD5 IGFBP5 MAP6 4 8 1 H, K,
  • SurvExpress an online biomarker validation tool and database for cancer gene expression data using survival analysis.
  • TNMplot.com A Web Tool for the Comparison of Gene Expression in Normal, Tumor and Metastatic Tissues. Int J Mol Sci 22. Gao, J., Aksoy, B.A., Dogrusoz, U., Dresdner, G., Gross, B., Sumer, S.O., Sun, Y., Jacobsen, A., Sinha, R., Larsson, E., Cerami, E., Sander, C., Schultz, N., 2013.
  • GENT2 an updated gene expression database for normal and tumor tissues.
  • the Human Protein Atlas as a proteomic resource for biomarker discovery.
  • comparing the determined expression levels with one or more reference values to identify any altered expression levels in the subject’s biological sample wherein altered expression levels of the ZNF92, ET-9, or nine or more of the ET- 60 biomarkers in the biological sample relative to the reference value indicates that the subject has cancer with poor prognosis or the subject has malignant cancer, and absence of altered expression of the ZNF92, ET-9, or nine or more of the ET-60 biomarkers relative to the reference value indicates that the subject does not have a cancer with poor prognosis or does not have malignant cancer; and optionally c.
  • histone deacetylase inhibitors ZNF92 inhibitors, histone demethylase inhibitors, mTOR inhibitors, polo-like kinase (PLK) inhibitors, heat shock factor inhibitors, or a combination thereof to a subject determined to have a cancer with poor prognosis or a malignant cancer.
  • ZNF92 inhibitors histone demethylase inhibitors
  • mTOR inhibitors histone demethylase inhibitors
  • mTOR inhibitors polo-like kinase (PLK) inhibitors
  • heat shock factor inhibitors or a combination thereof to a subject determined to have a cancer with poor prognosis or a malignant cancer.
  • a method of treating a subject classified as having poor cancer prognosis comprising administering one or more histone deacetylase inhibitors, ZNF92 inhibitors, histone demethylase inhibitors, mTOR inhibitors, polo-like kinase inhibitors, heat shock factor inhibitors, or a combination thereof to the subject, wherein the subject is classified has having poor cancer prognosis by measuring expression levels of at least one sample from the subject and determining that the at least one sample has altered expression of the ZNF92, ET-9, or nine or more of the ET-60 biomarkers relative to at least one reference value.
  • a method comprising treating a subject having altered expression of ZNF92, ET-9 biomarkers, or nine or more of the ET-60 biomarkers relative to at least one reference value, by administering one or more histone deacetylase inhibitors, ZNF92 inhibitors, histone demethylase inhibitors, mTOR inhibitors, polo-like kinase inhibitors, heat shock factor inhibitors, or a combination thereof to the subject.
  • the one or more reference values is an average or median of expression levels of at least the ZNF92, ET-9, or ET-60 biomarkers in biological samples from a population of healthy subjects. 5.
  • the method of statement 1-3, or 4 wherein the subject has, or is suspected of having, breast cancer, ovarian cancer, colon cancer, brain cancer, pancreatic cancer, prostate cancer, lung cancer, melanoma, leukemia, myeloma, or lymphoma. 6.
  • the method of statement 1-4, or 5 wherein the subject has breast cancer.
  • the method of statement 1-5 or 6, wherein the altered expression of one or more of the ZNF92, ET-9, or nine or more of the ET-60 biomarkers is increased expression relative to the reference value.
  • 8. The method of statement 1-5 or 6, wherein the altered expression of one or more of the ZNF92, ET-9, or nine or more of the ET-60 biomarkers is decreased expression relative to the reference value.
  • the method of statement 1-7 or 8, wherein the altered expression of the ZNF92, ET-9, or nine or more of the ET-60 biomarkers relative to the reference value is a difference of at least 10% as compared to a reference level, or of at least about 20%, or at least about 30%, or at least about 40%, or at least about 50%, or at least about 60%, or at least about 70%, or at least about 80%, or at least about 90% or up to and including a 100% increase or any increase between 10-100% as compared to a reference value, or at least about a 1.5-fold, at least about a 1.6-fold, at least about a 1.7-fold, at least about a 1.8-fold, at least about a 1.9-fold, at least about a 2-fold, at least about a 3-fold, or at least about a 4-fold, or at least about a 5-fold, at least about a 10-fold compared to the reference value.
  • a method comprising: (a) contacting ZNF92-expressing cells or ZNF92 proteins with a test agent; (b) measuring ZNF92 expression (mRNA or protein) levels in the cells or measuring ZNF92 protein activity levels; and (c) determining that the test agent reduces the expression levels or activity levels of ZNF92, to thereby identifying a test agent as a candidate agent that reduces ZNF92 expression levels or activity levels. 11.
  • a method comprising: (a) contacting cells that expression one or more ET-9 or ET-60 biomarkers with a test agent; (b) measuring expression (mRNA or protein) levels or measuring activity levels of the one or more ET-9 or ET-60 biomarkers; and (c) determining that the test agent reduces the expression levels or activity levels of the one or more ET-9 or ET-60 biomarkers, to thereby identifying a test agent as a candidate agent that reduces one or more ET-9 or ET-60 biomarkers expression levels or activity levels.

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  • Biochemistry (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • General Engineering & Computer Science (AREA)
  • Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)

Abstract

L'invention concerne des méthodes précises de détection du cancer et de détermination du pronostic du cancer, notamment du cancer du sein, à l'aide de biomarqueurs appelés ici biomarqueurs ET-9 et ET-60. Par exemple, ZNF92 s'avère être étonnamment spécifique pour le cancer du sein. L'invention concerne également des méthodes de traitement de patients cancéreux catégorisés comme ayant un mauvais pronostic par les méthodes de l'invention.
EP22854712.1A 2021-12-22 2022-12-22 Signature de cancer du sein épigénétique pronostique/prédictive Pending EP4453261A1 (fr)

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WO2025122992A1 (fr) * 2023-12-08 2025-06-12 Cornell University Signatures d'ascendance cellulaire pour le sous-typage de priorité de cancers

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US4683202A (en) 1985-03-28 1987-07-28 Cetus Corporation Process for amplifying nucleic acid sequences
US4843155A (en) 1987-11-19 1989-06-27 Piotr Chomczynski Product and process for isolating RNA
US5800992A (en) 1989-06-07 1998-09-01 Fodor; Stephen P.A. Method of detecting nucleic acids
US6040138A (en) 1995-09-15 2000-03-21 Affymetrix, Inc. Expression monitoring by hybridization to high density oligonucleotide arrays
CA2118806A1 (fr) 1991-09-18 1993-04-01 William J. Dower Methode pour la synthese de diverses series d'oligomeres
US5384261A (en) 1991-11-22 1995-01-24 Affymax Technologies N.V. Very large scale immobilized polymer synthesis using mechanically directed flow paths
AU675054B2 (en) 1991-11-22 1997-01-23 Affymetrix, Inc. Combinatorial strategies for polymer synthesis
US5856174A (en) 1995-06-29 1999-01-05 Affymetrix, Inc. Integrated nucleic acid diagnostic device
US5854033A (en) 1995-11-21 1998-12-29 Yale University Rolling circle replication reporter systems
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DE69829402T2 (de) 1997-10-31 2006-04-13 Affymetrix, Inc. (a Delaware Corp.), Santa Clara Expressionsprofile in adulten und fötalen organen
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US20180275129A1 (en) * 2014-03-18 2018-09-27 Sanford Health Reagents and Methods for Breast Cancer Detection
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US20170002319A1 (en) * 2015-05-13 2017-01-05 Whitehead Institute For Biomedical Research Master Transcription Factors Identification and Use Thereof
US11279765B2 (en) * 2017-07-08 2022-03-22 The General Hospital Corporation Compositions and methods to improve anti-angiogenic therapy and immunotherapy

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WO2023122758A1 (fr) 2023-06-29

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